Today is just a quick little follow-up to my post from Monday. There I talked about how a Boston Globe piece using three-dimensional columns to show snowfall amounts in last weekend’s blizzard failed to clearly communicate the data. Then I showed a map from the National Weather Service (NWS) that showed the snowfall ranges over an entire area.
Well scrolling through the weather feeds on the Twitter yesterday I saw this graphic from the NWS that comes closer to the Globe‘s original intent, but again offers a far clearer view of the data.
Whilst we miss individual reports being depicted as exact, that is to say the reports are grouped into bins and assigned a colour, we have a much more granular view than we did with the first NWS graphic I shared.
The only comment I have on this graphic is that I would probably drop the terrain element of the map. The dots work well when placed atop the white map, but the lighter blues and yellows fade out of view when placed atop the green.
But overall, this is a much clearer view of the storm’s snowfall.
Credit for the piece goes to the National Weather Service graphics department.
On Friday, I mentioned in brief that the East Coast was preparing for a storm. One of the cities the storm impacted was Boston and naturally the Boston Globecovered the story. One aspect the paper covered? The snowfall amounts. They did so like this:
This graphic fails to communicate the breadth and literal depth of the snow. We have two big reasons for that and they are both tied to perspective.
First we have a simple one: bars hiding other bars. I live in Greater Centre City, Philadelphia. That means lots of tall buildings. But if I look out my window, the tall buildings nearer me block my view of the buildings behind. That same approach holds true in this graphic. The tall red columns in southeastern Massachusetts block those of eastern and northeastern parts of the state and parts of New Hampshire as well. Even if we can still see the tops of the columns, we cannot see the bases and thus any real meaningful comparison is lost.
Second: distance. Pretty simple here as well, later today go outside. Look at things on your horizon. Note that those things, while perhaps tall such as a tree or a skyscraper, look relatively small compared to those things immediately around you. Same applies here. Bars of the same data, when at opposite ends of the map, will appear sized differently. Below I took the above screenshot and highlighted two observations that differed in only 0.5 inches of snow. But the box I had to draw—a rough proxy for the columns’ actual heights—is 44% larger.
This map probably looks cool to some people with its three-dimensional perspective and bright colours on a dark grey map. But it fails where it matters most: clearly presenting the regional differences in accumulation of snowfall amounts.
Compare the above to this graphic from the Boston office of the National Weather Service (NWS).
No, it does not have the same cool factor. And some of the labelling design could use a bit of work. But the use of a flat, two-dimensional map allows us to more clearly compare the ranges of snowfall and get a truer sense of the geographic patterns in this weekend’s storm. And in doing so, we can see some of the subtleties, for example the red pockets of greater snowfall amounts amid the wider orange band.
Credit for the Globe piece goes to John Hancock.
Credit for the NWS piece goes to the graphics department of NWS Boston.
When the remnants of Hurricane Ida rolled through the Northeast two weeks ago, here in the Philadelphia region we saw catastrophic flooding from deluges west of the city and to the east we had a tornado outbreak in South Jersey. At a simplistic level we can attribute the differences in outcomes to the path of the storm. As Ida was no longer a hurricane she developed what we call warm and cold sectors along the frontal boundary. Long story short, we can see different types of weather in these setups with heavy rain in the cold and severe weather in the warm. And that’s what we saw with Ida: heavy, flood-causing rains in the cold sector north and west of Philadelphia and then severe weather, tornadoes, in the warm sector south and east of the city.
But I want to talk about the tornadoes, and one in particular: an EF3 tornado that struck the South Jersey town of Mullica Hill. EF3 refers to the enhanced Fujita scale that describes the severity of tornadoes. EF1s are minor and EF5s are the worst. The Philadelphia region has in the past rarely seen tornadoes, but even moderate strength ones such as an EF3 are almost unheard of in the area.
This tornado caused significant damage to the area, but was also remarkable because it persisted for 12 miles. Most tornadoes dissipate in a fraction of that length. The Mount Holly office of the National Weather Service (NWS) produced a few graphics detailing tornadoes Ida spawned. You can see from the timeline graphic that the Mullica Hill tornado was particularly long lasting in time as well as distance travelled, surviving for twenty minutes.
To briefly touch on the design of this graphic, I think it generally works well. I’m not certain if the drop shadow adds anything to the graphic and I might have used a lighter colour text label for the times as they fight with the graphical components for visual primacy. Secondly, I’m not certain that each tornado needs to be in a different colour. The horizontal rules keep each storm visually separate. Colour could have instead been used to indicate perhaps peak severity for each tornado or perhaps at specific moments in the tornadoes’ lives. But overall, I like this graphic.
NWS Mt Holly also produced a graphic specifically about the tornado detailing its path.
Here we have a graphic incorporating what looks like Google Earth or Google Maps imagery of the area and an orange line denoting the path. At various points faint text labels indicate the strength of the tornado along its path. A table to the left provides the key points.
From a graphical standpoint, I think this could use a bit more work. The orange line looks too similar to the yellow roads on the map and at a quick glance may be too indistinguishable. Compare this approach to that of the Philadelphia Inquirer in its writeup.
Here we have a map with desaturated colours with a bright red line that clearly sets itself apart from the map. I think a similar approach would have benefitted the NWS graphic. Although the NWS graphic does have a stroke weight that varies depending upon the path of the tornado.
I also have a graphic made by a guy I know who lives in the area. He took that maximum tornado width of 400 yards and used screenshots of Google Maps in combination with his own direct evidence and photos and videos from his neighbours and their social media posts to try and plot the tornado’s path more granularly. Each red mark represents storm damage and a width of 400 yards.
I’m not going to critique this graphic because he made it more for himself to try and understand how close he was to the storm. In other words, it wasn’t meant to be published. But I’m thankful he allowed me to share it with you. But even here you can see he chose a colour that contrasted strongly with the background satellite views.
All of this just goes to show you the path and devastation one tornado caused. And that one tornado was just a fraction of the devastation Ida wrought upon the Northeast let alone the rest of the United States.
The middle third of the United States sits under some pretty cold Arctic air, helping to bring frozen precipitation, i.e. snow, to places unfamiliar with it, most notably Texas. I say unfamiliar, but Texas is also negligently unprepared. There are photos circulating the internet of Texarkana, a city straddling the Texas–Arkansas border, of the Arkansas side plowed and safe for travel whilst the Texas side…is not. You also have a deregulated and privatised energy grid, which has seen wholesale prices spike to $9,000 per megawatt hour. (Some companies in the Texan market charge wholesale rates to their customers, so I wouldn’t be surprised to see stories coming out in the next few weeks of excessively large electric bills.)
What’s driving this Texas-scale cold? Why is Arctic air over Dallas? In years past you’ve probably heard the term “polar vortex”. The super simple version is that really cold air spins in a tight upper-atmosphere vortex over the pole, hence the name. But when the vortex weakens, say due to warmer air, it becomes a bit more unstable. When it becomes unstable, a chunk of it might break off and descend south. It doesn’t always descend over continental North America, but when it does… well, since the mid 2010s we’ve been calling it the polar vortex. Keep in mind, that it’s not, it’s a part of an upper-level low whose cold air eventually falls to the surface, but despite my protestations, the name has stuck.
Anyway, it means we presently are witnessing some frigid temperatures across the US and this graphic from the National Weather Service (NWS) highlights just how extreme those temperatures are.
The distance is no surprise here, because in winter one would expect Minneapolis and Miami to exhibit extreme temperature differences. But it’s the scale of this difference that is so dramatic.
I could probably do a whole piece—or several—about the design of NWS graphics, but I’ll just point out that I’d probably lighten the black lines working as state/provincial borders. And while their colours are standardised, I wonder if making a clearer distinction between freezing and above freezing (32ºF in this map) would make some more sense.
In a first, the Gulf of Mexico basin has two active hurricanes simultaneously. Unfortunately, they are both likely to strikes somewhere along the Louisiana coastline within approximately 36 hours of each other. Fortunately, neither is strong as a storm named Katrina that caused a mess of things several years ago now.
Over the last few weeks I have been trying to start the week with my Covid datagraphics, but I figured we could skip those today and instead run with this piece from the Washington Post. It tracks the forecast path and forecast impact of tropical storm force winds for both storms.
The forecast path above is straight forward. The dotted line represents the forecast path. The coloured area represents the probability of that area receiving tropical storm force winds. Unsurprisingly the present locations of both storms have the greatest possibilities.
Now compare that to the standard National Weather Service graphic, below. They produce one per storm and I cannot find one of the combined threat. So I chose Laura, the one likely to strike mid-week and not the one likely to strike later today.
The first and most notable difference here is the use of colour. The ocean here is represented in blue compared to the colourless water of the Post version. The colour draws attention to the bodies of water, when the attention should be more focused on the forecast path of the storm. But, since there needs to be a clear delineation between land and water, the Post uses a light grey to ground the user in the map (pun intended).
The biggest difference is what the coloured forecast areas mean. In the Post’s versions, it is the probability of tropical force winds. But, in the National Weather Service version, the white area actually is the “cone”, or the envelope or range of potential forecast paths. The Post shows one forecast path, but the NWS shows the full range and so for Laura that means really anywhere from central Louisiana to eastern Texas. A storm that impacts eastern Texas, for example, could have tropical storm force winds far from the centre and into the Galveston area.
Of course every year the discussion is about how people misinterpret the NWS version as the cone of impact, when that is so clearly not the case. But then we see the Post version and it might reinforce that misconception. Though, it’s also not the Post’s responsibility to make the NWS graphic clearer. The Post clearly prioritised displaying a single forecast track instead of a range along with the areas of probabilities for tropical storm force winds.
I would personally prefer a hybrid sort of approach.
But I also wanted to touch briefly on a separate graphic in the Post version, the forecast arrival times.
This projects when tropical storm force winds will begin to impact particular areas. Notably, the areas of probability of tropical storm force winds does not change. Instead the dotted line projections for the paths of the storms are replaced by lines relatively perpendicular to those paths. These lines show when the tropical storm winds are forecast to begin. It’s also another updated design of the National Weather Service offering below.
Again, we only see one storm per graphic here and this is only for Laura, not Marco. But this also probably most analogous to what we see in the Post version. Here, the black outline represents the light pink area on the Post map, the area with at least a 5% forecast to receive tropical storm force winds. The NWS version, however, does not provide any further forecast probabilities.
The Post’s version is also design improved, as the blue, while not as dark the heavy black lines, still draws unnecessary attention to itself. Would even a very pale blue be an improvement? Almost certainly.
In one sense, I prefer the Post’s version. It’s more direct, and the information presented is more clearly presented. But, I find it severely lack in one key detail: the forecast cone. Even yesterday, the forecast cone had Laura moving in a range both north and south of the island of Cuba from its position west of Puerto Rico. 24 hours later, we now know it’s on the southern track and that has massive impact on future forecast tracks.
Being east of west of landfall can mean dramatically different impacts in terms of winds, storm surge, and rainfall. And the Post’s version, while clear about one forecast track, obscures the very real possibilities the range of impacts can shift dramatically in just the course of one day.
I think the Post does a better job of the tropical storm force wind forecast probabilities. In an ideal world, they would take that approach to the forecast paths. Maybe not showing the full spaghetti-like approach of all the storm models, but a percentage likelihood of the storm taking one particular track over another.
Credit for the Post pieces goes to the Washington Post graphics department.
Credit for the National Weather Service graphics goes to the National Weather Service.
I mean come on, guys, did you really expect me to not touch this one?
Well we made it to Friday, and naturally in the not so serious we have to cover the sharpie map. Because, if the data does not agree with your opinions, clearly the correct response is to just make shit up.
By now you have probably all heard the story about how President Trump tweeted an incorrect forecast about the path of Hurricane Dorian, warning how Alabama could be “hit (much) harder than anticipated”. Except that the forecast at the time was that Alabama wasn’t going to be hit. Cue this map, days later. As in days. As in this news story continued for days.
So to be fair, I went to the NOAA website and pulled down from their archive the cone maps from the date of the graphic Trump edited, and the one from the day when he tweeted about Alabama being hit by the hurricane.
Important to note that this forecast dates from 29 August. This press conference was on 4 September. He tweeted on 1 September. So in other words, two days after he used the wrong forecast, he had printed a big version of a contemporaneously two-day old forecast to show that if he drew a sharpie line on it, it would be correct.
Here is the original, from the National Hurricane Centre, for 29 August. Note, no Alabama.
And then Trump tweeted on 1 September. So let’s take the 02.00 Eastern time 1 September forecast from NOAA.
Definitely no Alabama in that forecast.
This could have all gone away if he had just admitted he looked at the wrong forecast and tweeted an incorrect warning. Instead, we had the White House pressuring NOAA to “fix” their tweet.
Now we can all chalk this up as funny. But it does have some serious consequences. Instead of people in the actual path of Dorian preparing, because of the falsely wide range of impacts the president suggested, people in Alabama needlessly prepared for a nonevent.
But more widely, as someone who works with data on a daily basis, we need to agree that data is real. We cannot simply change the data because it does not fit the story we want to tell. If I could take a screenshot of every forecast and string them together in an animated clip, you would see there was never any forecast like the sharpie forecast. We cannot simply create our own realities and choose to live within them, because that means we have no common basis on which to disagree policy decisions that will have real world impacts.
Credit for the photo goes to Evan Vucci of the AP.
Credit for the National Hurricane Centre maps goes to its graphic team.
Today, 9 February, it finally snowed significantly here in Philadelphia. In Chicago it probably snowed shortly after I moved out in September. Today’s graphic is a forecast map from philly.com using National Weather Service (NWS) data.
I fail to understand the divergent palette—to be fair this is not the only instance of it throughout the meteorological world. There is a split at the six-inch mark—but why? If anything, my eye would think that the 4–6 range is the heaviest, not the yellow. Snowfall is usually more of a continuous range, and so both within the blues and yellows you get that through a softer edge as the colours become more intense. And then you hit the six-inch mark and a violent shift.
I am also curious as to why the choice to use a coloured map background. Especially if the colour, a lightish green-blue is so close to the lightish blue used by the map to forecast snowfall.
In short, I think this Philadelphia map could use some attention from some designers to make the message a bit clearer.
Credit for the piece goes to the philly.com graphics department.
If you live in the United States, you probably have heard the term polar vortex by now. People have been using the term to describe the bitterly cold temperatures affecting the eastern two-thirds of the country. But the term polar vortex is a meteorological term that means a specific phenomenon. In other words, it’s more than a hashtag along the lines of snowmageddon. The Washington Post explains what the polar vortex is.
My caveat for this piece is that from my understanding, it’s not entirely correct. Or perhaps not detailed enough. In brief, we turn to the National Weather Service out of New York for a more technically correct, but more poorly designed graphic.
Poor type, poor colours, poor hierarchy. Those are abundantly clear, but the important part is that the NWS wants to correct many of the popular misconceptions. Somewhere between the well-intended but less-than-entirely-clear Post piece and the accurate-but-also-unclear National Weather Service piece is an opportunity to explain the concept to the public.
Credit for the Washington Post piece goes to Bonnie Berkowitz, Richard Johnson, Katie Park, and Gene Thorp.
Credit for the National Weather Service goes to the graphics team at the National Weather Service of New York.